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The EnSeal™ PTC TRIO of the EnSeal™ Vessel Sealing and Hemostasis system is a bioolar electrosurgical instrument for use with a radiofrequency generator. It is intended for use during open or laparoscopic, general and gynecologic surgery to cut and seal vessels, cut, grasp and dissect tissue during surgery.

Indications for use include open and laparoscopic general and gynecological surgical procedures (including urologic, thoracic, plastic and reconstructive, bowel resections, hysterectomies, cholecystectomies, gall bladder procedures, Nissen fundoplication, adhesiolysis, oophorectomies, etc.), or any procedure where vessel ligation (cutting and sealing), tissue grasping and dissection is performed. The devices can be used on vessels up to (and including) 7 mm and bundles as large as will fit in the jaws of the instruments.

The SurgRx EnSeal Vessel Sealing & Hemostasis System has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use this system for these procedures.

EnSeal™ Vessel Sealing and Hemostasis System. The functionality of the System is the same as the predicate device.

The provided 510(k) summary for the EnSeal™ PTC TRIO of the EnSeal™ Vessel Sealing & Hemostasis System does not contain sufficient information to fulfill all aspects of your request regarding acceptance criteria and a detailed study.

Here's what can be extracted based on the provided text, and where information is missing:

Missing Information:
The document primarily focuses on establishing substantial equivalence to a predicate device based on the functionality of the system and preclinical laboratory (bench) and performance tests. It does not detail specific acceptance criteria with numerical targets or comprehensive clinical study results. There is no mention of a test set, ground truth experts, adjudication methods, multi-reader multi-case studies, standalone algorithm performance, or training set details. This is typical for a 510(k) submission that relies on substantial equivalence to a predicate device for safety and effectiveness, rather than a de novo or PMA submission requiring extensive clinical trial data detailing explicit performance metrics.

1. Table of Acceptance Criteria and Reported Device Performance

Detailed Study Information (Based on available text):

2. Sample size used for the test set and the data provenance:

• Not explicitly stated. The document refers to "Preclinical laboratory (bench) and performance tests" and "design validation" without providing details on specific sample sizes for these tests or the origin of any data used.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable / Not mentioned. The submission describes device testing (likely in a lab/bench setting), not a study requiring expert-established ground truth for diagnostic accuracy.

4. Adjudication method for the test set:

• Not applicable / Not mentioned. This type of adjudication is typically for clinical or diagnostic accuracy studies, which are not detailed here.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No. An MRMC study is not mentioned. This device is an electrosurgical instrument, not an AI diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• No. This is an electrosurgical instrument for human use, not an algorithm.

7. The type of ground truth used:

• Not applicable / Not mentioned. For bench and performance tests of a surgical instrument, "ground truth" would likely relate to objective measurements of sealing strength, cut efficacy, temperature profiles, etc., against predefined engineering or performance specifications. The document states "Preclinical laboratory (bench) and performance tests were executed to ensure the devices function as intended and meet design specifications."

8. The sample size for the training set:

• Not applicable / Not mentioned. This is not a machine learning or AI device that would typically involve a "training set."

9. How the ground truth for the training set was established:

• Not applicable / Not mentioned. See point 8.

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